Competing interactions in two dimensional Coulomb systems: Surface charge heterogeneities in co-assembled cationic-anionic incompatible mixtures

TL;DR

This study investigates how competing short-range and long-range electrostatic interactions influence microphase segregation in two-dimensional Coulomb systems, using analytical methods and molecular dynamics simulations to reveal domain formation and effects of salt addition.

Contribution

It provides a combined analytical and simulation analysis of surface charge heterogeneities in 2D Coulomb systems, highlighting the effects of interaction strengths and salt on domain structures.

Findings

Well-defined domains form depending on interaction balance

Salt addition disrupts domain ordering and promotes macroscopic phase separation

Analytical predictions align with simulation results

Abstract

A binary mixture of oppositely charged components confined to a plane such as cationic and anionic lipid bilayers may exhibit local segregation. The relative strength of the net short range interactions, which favors macroscopic segregation, and the long range electrostatic interactions, which favors mixing, determines the length scale of the finite size or microphase segregation. The free energy of the system can be examined analytically in two separate regimes, when considering small density fluctuations at high temperatures, and when considering the periodic ordering of the system at low temperatures (F. J. Solis and M. Olvera de la Cruz, J. Chem. Phys. 122, 054905 (2000)). A simple Molecular Dynamics simulation of oppositely charged monomers, interacting with a short range Lennard Jones potential and confined to a two dimensional plane, is examined at different strengths of short and long range interactions. The system exhibits well-defined domains that can be characterized by their periodic length-scale as well as the orientational ordering of their interfaces. By adding salt, the ordering of the domains disappears and the mixture macroscopically phase segregates in agreement with analytical predictions.